Dear R community,
I would like to compare the degree of aggregation (or dispersion) of
bacteria isolated from plant material. My data are discrete counts
from leaf washes. While I do have xy coordinates for each plant, it
is aggregation in the sense of the concentration of bacteria in high
density patches that I am interested in.
My attempt to analyze this was to fit negative binomial glms to each
of my leaf treatments (using MASS) and to compare estimates of theta
and use the standard errors to calculate confidence limits. My
values of theta (se) were 0.387 (0.058) and 0.1035 (0.015) which were
in the right direction for my hypothesis. However, some of the stats
literature suggests that the confidence intervals of theta (or k) are
not very robust and it would be better to calculate confidence
intervals for 1/k. Is there a way I can estimate confidence intervals
for 1/k in R, or indeed a more elegant way of looking at aggregation?
Many thanks for your time.
yours,
Dr Ben Raymond,
NERC Advanced Research Fellow,
Lecturer in Population Genetics,
School of Biological Sciences,
Royal Holloway University of London,
Egham,
Surrey.
TW20 0EX
tel 0044 1784443547
ben.raym...@rhul.ac.uk
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